Text Steganography has become a dominant research field in information sharing domain and many researches are being conducted to strengthen this area. Researches around the amount of secret message that could be stored in a given cover image is always critical for any steganography technique used to share the secret text. This research paper proposes an enhanced Least Significant Bit (eLSB) embedding technique in steganography, through which the quality of cover image is improved, when compared to typical LSB algorithm used in steganography. The proposed method employs in spatial domain and it does the secret message encoding in two phases. The first phase generates the metadata and embeds the header information in first few bytes of cover image and then the following phase takes care of processing secret message and storing the secret message in cover image using an optimized way, which is possible through analyzing secret text's character sequences. Proposed work results into occupying lesser space for the given secret text in cover image and hence leads to the better stego image quality than existing LSB algorithms. As the algorithm works on optimizing secret message during embedding phase itself, this technique enables high capacity embedding rate, additional security due to secret message preprocessing and enhanced cover image quality. The results are compared with LSB algorithm and compared to Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Root Mean Square Error (RMSE) values to prove the proposed algorithm performs better on secret text embedding in cover image.

In this research work, proposing an algorithm, which dynamically selects the best compression algorithms among several compression techniques for steganography encoding. Ranking and selection of best algorithm for each and every steganographic transaction is based on several factors like type of cover image being used for the transmission, length of the secret message, type of the message, compression ratio of the secret message being shared, encoding ratio of secret message over the medium etc., The proposed algorithm dynamically ranks and selects the right compression algorithm to be used for the given secret file to occupy lesser embedding space in stego-image.

In this proposed research work, an attempt has been made to use multiple image files for steganography encoding along with the capability of secret text recovery in the event of any image corruption during the transit. This algorithm is effective on the security factor of secret image since the embedded checksum will validate for any unauthorized users or intruders attempt to corrupt the picture in any aspect. If any of the stego image underwent any steganalysis or MiM attack, then this proposed algorithm can effectively regenerate the content of one stego image using other intact stego images received in the receiving end.